DM: How to improve the decision tree's generalization performance

[fardin akbaryan]

    In my research, I am using the decision tree( C4.5) as a 
classifier.

The available training data set for my research do not cover all the
input space which is common in classification methods. I have observed
that the performance of the tree on the unseen patterns is poor. In
another word, my classifier lacks the reliability in terms of the
generalization. As you know there are many methods and theories to
improve the classifier's capability for the generalization. But I need
to have a method specifically for a decision tree.  I'll really
appreciate
if you give me a clue about this matter. Thanks in advance for your
help.

Fardin
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Fardin Akbaryan
Chemical and Petroleum Eng. Department
University of Calgary
2500 University Drive NW
Calgary T2N 1N4, Alberta, Canada
Tel: (403) 220-7409
Fax: (403) 284-4852